Adopting AI

 While the hype and market valuations sky rocketed about AI since ChatGPT launch, mass adoption especially with enterprises need AI to cross some significant thresholds:

1. Explainable: Every decision/recommendation needs to be 'explainable' in terms of how it is arrived at, what is the basis, how robust is the deductive logic and also how easy is it for regulators to understand and be comfortable with the rationale .
2. Consistent and Repeatable: Many business processes expect and demand consistency and repeatability. Same question or transaction needs the same answer or decision every time. Consistent client experience , regulatory compliance , profitability and risk management cannot be ensured otherwise.
3. Transparent: Wide spread adoption also demands simplicity and transparency. Decision/recommendation/output cannot hide behind complex mathematics/models that cannot be interpreted easily.
4. Ethical: Guard rails to ensure the AI output meets the standards of Common Good, Socially acceptable norms in the culture and legal righteousness. Historical biases due to the nature of data, discrimination, sensitivities to user age etc - how are these addressed?
5. Secure : How secure and private is the input data? How is the balance achieved between global learnings and local data privacy ? How tamper proof are the results?
6. Better than human : As governments and economies push job creation, can AI be at least as good as human, if not better? In a number of situations, humans are better than machines due to a variety of factors.